Keywords Spatial analysis, Setup, GRASS, SAGA, OTB, QGIS Despite the well known capabilities of spatial analysis and data handling in the world of R, an enormous gap persists between R and the mature open source Geographic Information System (GIS) and Remote Sensing (RS) software community. Prominent representatives like QGIS, GRASS GIS and SAGA GIS provide comprehensive and continually growing collections of highly sophisticated algorithms that are mostly fast, stable and usually well proofed by the community Although a number of R wrappers aim to bridge this gap (eg rgrass7 for GRASS GIS 7.x, RSAGA for SAGA GIS) – among which RQGIS is the most recent outcome to realize a simple access to the powerful QGIS command line interface – most of these packages are not that easy to setup. Most of the wrappers are trying to find and/or set an appropriate environment, nevertheless it is in many cases at least cumbersome to get all necessary settings correct, especially if one has to work with restricted rights or parallel installations of the same GIS software. In order to overcome known limitations, the package link2GI provides a small framework for easy linking of R to major GIS software. Here, linking simply means to provide all necessary environment settings as well as full access to the command line APIs of these software tools, whereby the strategy differs from software to software. As a result an easy entrance door for linking current versions of GRASS7.x GIS, SAGAGIS, QGIS as well as other command line tools like the Orfeo Toolbox (OTB) to R is provided. The package focus on both R users that are not very familiar with the conditions and pitfalls of their preferred operating system and more experienced users that want to have some comfortable shortcuts for a seamless integration of e.g. GRASS. The most simple call link2GI::linkGRASS7(x=anySpatialObject) will search for the OS dependent installations of GRASS 7. Furthermore, it will setup the rsession according to the provided spatial object. All steps can be influenced manually which will significantly speed up the process. Especially if you work with already established GRASS databases it provides a convenient way to link mapsets and locations correctly. The package is also providing some basic tools beyond simple linking. Since Edzer Pebesma’s new sf package, it is for the first time possible to deal with big vector data sets (> 1.000.000 polygons or 25.000.000 vertices). Nevertheless it is advantagous to process the more sophisticeded spatial analysis with external GIS software. To improve this process link2GI provides a first version of direct reading and writing GRASS and SAGA vector data from and to R to speed up the conversion process. Finally, a first version of a common Orfeo Toolbox wrapper for simplifying OTB calls is introduced.
